{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 19,
   "source": [
    "import pandas as pd\r\n",
    "import numpy as np\r\n",
    "import matplotlib.pyplot as plt"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "source": [
    "reader = pd.ExcelFile('../2021-01-01to2021-03-01provincetoprovince.xlsx')"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "source": [
    "dfs = []\r\n",
    "for sheet in reader.sheet_names:\r\n",
    "    df = reader.parse(sheet_name=sheet)\r\n",
    "    dfs.append(df)\r\n",
    "concat_dfs = pd.concat(dfs,axis=0)"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "source": [
    "concat_dfs.head()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "   Unnamed: 0 o_province  2021-01-01 d_province  2021-01-02  2021-01-03  \\\n",
       "0           0        河北省       46.77        北京市       57.55       61.18   \n",
       "1           1        天津市        9.49        北京市        7.68        8.09   \n",
       "2           2        山东省        5.62        北京市        4.83        5.04   \n",
       "3           3        河南省        4.10        北京市        3.82        3.65   \n",
       "4           4        广东省        3.05        北京市        1.82        1.39   \n",
       "\n",
       "   2021-01-04  2021-01-05  2021-01-06  2021-01-07  ...  2021-02-20  \\\n",
       "0       59.34       47.15       47.10       49.12  ...       40.53   \n",
       "1        9.56        7.14        6.55        7.32  ...        4.01   \n",
       "2        5.77        6.89        6.97        6.00  ...        8.27   \n",
       "3        4.28        5.96        5.77        4.96  ...       10.46   \n",
       "4        1.22        2.03        2.07        2.24  ...        1.13   \n",
       "\n",
       "   2021-02-21  2021-02-22  2021-02-23  2021-02-24  2021-02-25  2021-02-26  \\\n",
       "0       38.93       43.07       40.48       38.29       42.86       40.57   \n",
       "1        3.96        5.78        5.05        4.62        5.12        5.96   \n",
       "2        8.65        7.15        7.10        7.21        6.23        5.60   \n",
       "3       11.28        9.52        9.01        9.55        6.86        6.46   \n",
       "4        1.12        1.17        1.48        1.63        1.85        2.01   \n",
       "\n",
       "   2021-02-27  2021-02-28  2021-03-01  \n",
       "0       44.45       36.85       45.94  \n",
       "1        5.39        3.81        6.53  \n",
       "2        6.86        8.45        6.97  \n",
       "3        6.39       12.15        7.89  \n",
       "4        1.86        1.41        1.50  \n",
       "\n",
       "[5 rows x 63 columns]"
      ],
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>o_province</th>\n",
       "      <th>2021-01-01</th>\n",
       "      <th>d_province</th>\n",
       "      <th>2021-01-02</th>\n",
       "      <th>2021-01-03</th>\n",
       "      <th>2021-01-04</th>\n",
       "      <th>2021-01-05</th>\n",
       "      <th>2021-01-06</th>\n",
       "      <th>2021-01-07</th>\n",
       "      <th>...</th>\n",
       "      <th>2021-02-20</th>\n",
       "      <th>2021-02-21</th>\n",
       "      <th>2021-02-22</th>\n",
       "      <th>2021-02-23</th>\n",
       "      <th>2021-02-24</th>\n",
       "      <th>2021-02-25</th>\n",
       "      <th>2021-02-26</th>\n",
       "      <th>2021-02-27</th>\n",
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       "      <th>2021-03-01</th>\n",
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       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>河北省</td>\n",
       "      <td>46.77</td>\n",
       "      <td>北京市</td>\n",
       "      <td>57.55</td>\n",
       "      <td>61.18</td>\n",
       "      <td>59.34</td>\n",
       "      <td>47.15</td>\n",
       "      <td>47.10</td>\n",
       "      <td>49.12</td>\n",
       "      <td>...</td>\n",
       "      <td>40.53</td>\n",
       "      <td>38.93</td>\n",
       "      <td>43.07</td>\n",
       "      <td>40.48</td>\n",
       "      <td>38.29</td>\n",
       "      <td>42.86</td>\n",
       "      <td>40.57</td>\n",
       "      <td>44.45</td>\n",
       "      <td>36.85</td>\n",
       "      <td>45.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>天津市</td>\n",
       "      <td>9.49</td>\n",
       "      <td>北京市</td>\n",
       "      <td>7.68</td>\n",
       "      <td>8.09</td>\n",
       "      <td>9.56</td>\n",
       "      <td>7.14</td>\n",
       "      <td>6.55</td>\n",
       "      <td>7.32</td>\n",
       "      <td>...</td>\n",
       "      <td>4.01</td>\n",
       "      <td>3.96</td>\n",
       "      <td>5.78</td>\n",
       "      <td>5.05</td>\n",
       "      <td>4.62</td>\n",
       "      <td>5.12</td>\n",
       "      <td>5.96</td>\n",
       "      <td>5.39</td>\n",
       "      <td>3.81</td>\n",
       "      <td>6.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>山东省</td>\n",
       "      <td>5.62</td>\n",
       "      <td>北京市</td>\n",
       "      <td>4.83</td>\n",
       "      <td>5.04</td>\n",
       "      <td>5.77</td>\n",
       "      <td>6.89</td>\n",
       "      <td>6.97</td>\n",
       "      <td>6.00</td>\n",
       "      <td>...</td>\n",
       "      <td>8.27</td>\n",
       "      <td>8.65</td>\n",
       "      <td>7.15</td>\n",
       "      <td>7.10</td>\n",
       "      <td>7.21</td>\n",
       "      <td>6.23</td>\n",
       "      <td>5.60</td>\n",
       "      <td>6.86</td>\n",
       "      <td>8.45</td>\n",
       "      <td>6.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>河南省</td>\n",
       "      <td>4.10</td>\n",
       "      <td>北京市</td>\n",
       "      <td>3.82</td>\n",
       "      <td>3.65</td>\n",
       "      <td>4.28</td>\n",
       "      <td>5.96</td>\n",
       "      <td>5.77</td>\n",
       "      <td>4.96</td>\n",
       "      <td>...</td>\n",
       "      <td>10.46</td>\n",
       "      <td>11.28</td>\n",
       "      <td>9.52</td>\n",
       "      <td>9.01</td>\n",
       "      <td>9.55</td>\n",
       "      <td>6.86</td>\n",
       "      <td>6.46</td>\n",
       "      <td>6.39</td>\n",
       "      <td>12.15</td>\n",
       "      <td>7.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>广东省</td>\n",
       "      <td>3.05</td>\n",
       "      <td>北京市</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.39</td>\n",
       "      <td>1.22</td>\n",
       "      <td>2.03</td>\n",
       "      <td>2.07</td>\n",
       "      <td>2.24</td>\n",
       "      <td>...</td>\n",
       "      <td>1.13</td>\n",
       "      <td>1.12</td>\n",
       "      <td>1.17</td>\n",
       "      <td>1.48</td>\n",
       "      <td>1.63</td>\n",
       "      <td>1.85</td>\n",
       "      <td>2.01</td>\n",
       "      <td>1.86</td>\n",
       "      <td>1.41</td>\n",
       "      <td>1.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 63 columns</p>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "execution_count": 5
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "source": [
    "d_beijing = concat_dfs[concat_dfs.d_province == '北京市']\r\n",
    "d_beijing = d_beijing.drop(labels='Unnamed: 0', axis=1)\r\n",
    "d_beijing.head()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "  o_province  2021-01-01 d_province  2021-01-02  2021-01-03  2021-01-04  \\\n",
       "0        河北省       46.77        北京市       57.55       61.18       59.34   \n",
       "1        天津市        9.49        北京市        7.68        8.09        9.56   \n",
       "2        山东省        5.62        北京市        4.83        5.04        5.77   \n",
       "3        河南省        4.10        北京市        3.82        3.65        4.28   \n",
       "4        广东省        3.05        北京市        1.82        1.39        1.22   \n",
       "\n",
       "   2021-01-05  2021-01-06  2021-01-07  2021-01-08  ...  2021-02-20  \\\n",
       "0       47.15       47.10       49.12       48.71  ...       40.53   \n",
       "1        7.14        6.55        7.32        9.25  ...        4.01   \n",
       "2        6.89        6.97        6.00        5.45  ...        8.27   \n",
       "3        5.96        5.77        4.96        4.48  ...       10.46   \n",
       "4        2.03        2.07        2.24        2.38  ...        1.13   \n",
       "\n",
       "   2021-02-21  2021-02-22  2021-02-23  2021-02-24  2021-02-25  2021-02-26  \\\n",
       "0       38.93       43.07       40.48       38.29       42.86       40.57   \n",
       "1        3.96        5.78        5.05        4.62        5.12        5.96   \n",
       "2        8.65        7.15        7.10        7.21        6.23        5.60   \n",
       "3       11.28        9.52        9.01        9.55        6.86        6.46   \n",
       "4        1.12        1.17        1.48        1.63        1.85        2.01   \n",
       "\n",
       "   2021-02-27  2021-02-28  2021-03-01  \n",
       "0       44.45       36.85       45.94  \n",
       "1        5.39        3.81        6.53  \n",
       "2        6.86        8.45        6.97  \n",
       "3        6.39       12.15        7.89  \n",
       "4        1.86        1.41        1.50  \n",
       "\n",
       "[5 rows x 62 columns]"
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       "      <th></th>\n",
       "      <th>o_province</th>\n",
       "      <th>2021-01-01</th>\n",
       "      <th>d_province</th>\n",
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       "      <th>2021-01-03</th>\n",
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       "      <th>2021-02-20</th>\n",
       "      <th>2021-02-21</th>\n",
       "      <th>2021-02-22</th>\n",
       "      <th>2021-02-23</th>\n",
       "      <th>2021-02-24</th>\n",
       "      <th>2021-02-25</th>\n",
       "      <th>2021-02-26</th>\n",
       "      <th>2021-02-27</th>\n",
       "      <th>2021-02-28</th>\n",
       "      <th>2021-03-01</th>\n",
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       "  </thead>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>河北省</td>\n",
       "      <td>46.77</td>\n",
       "      <td>北京市</td>\n",
       "      <td>57.55</td>\n",
       "      <td>61.18</td>\n",
       "      <td>59.34</td>\n",
       "      <td>47.15</td>\n",
       "      <td>47.10</td>\n",
       "      <td>49.12</td>\n",
       "      <td>48.71</td>\n",
       "      <td>...</td>\n",
       "      <td>40.53</td>\n",
       "      <td>38.93</td>\n",
       "      <td>43.07</td>\n",
       "      <td>40.48</td>\n",
       "      <td>38.29</td>\n",
       "      <td>42.86</td>\n",
       "      <td>40.57</td>\n",
       "      <td>44.45</td>\n",
       "      <td>36.85</td>\n",
       "      <td>45.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>天津市</td>\n",
       "      <td>9.49</td>\n",
       "      <td>北京市</td>\n",
       "      <td>7.68</td>\n",
       "      <td>8.09</td>\n",
       "      <td>9.56</td>\n",
       "      <td>7.14</td>\n",
       "      <td>6.55</td>\n",
       "      <td>7.32</td>\n",
       "      <td>9.25</td>\n",
       "      <td>...</td>\n",
       "      <td>4.01</td>\n",
       "      <td>3.96</td>\n",
       "      <td>5.78</td>\n",
       "      <td>5.05</td>\n",
       "      <td>4.62</td>\n",
       "      <td>5.12</td>\n",
       "      <td>5.96</td>\n",
       "      <td>5.39</td>\n",
       "      <td>3.81</td>\n",
       "      <td>6.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>山东省</td>\n",
       "      <td>5.62</td>\n",
       "      <td>北京市</td>\n",
       "      <td>4.83</td>\n",
       "      <td>5.04</td>\n",
       "      <td>5.77</td>\n",
       "      <td>6.89</td>\n",
       "      <td>6.97</td>\n",
       "      <td>6.00</td>\n",
       "      <td>5.45</td>\n",
       "      <td>...</td>\n",
       "      <td>8.27</td>\n",
       "      <td>8.65</td>\n",
       "      <td>7.15</td>\n",
       "      <td>7.10</td>\n",
       "      <td>7.21</td>\n",
       "      <td>6.23</td>\n",
       "      <td>5.60</td>\n",
       "      <td>6.86</td>\n",
       "      <td>8.45</td>\n",
       "      <td>6.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>河南省</td>\n",
       "      <td>4.10</td>\n",
       "      <td>北京市</td>\n",
       "      <td>3.82</td>\n",
       "      <td>3.65</td>\n",
       "      <td>4.28</td>\n",
       "      <td>5.96</td>\n",
       "      <td>5.77</td>\n",
       "      <td>4.96</td>\n",
       "      <td>4.48</td>\n",
       "      <td>...</td>\n",
       "      <td>10.46</td>\n",
       "      <td>11.28</td>\n",
       "      <td>9.52</td>\n",
       "      <td>9.01</td>\n",
       "      <td>9.55</td>\n",
       "      <td>6.86</td>\n",
       "      <td>6.46</td>\n",
       "      <td>6.39</td>\n",
       "      <td>12.15</td>\n",
       "      <td>7.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>广东省</td>\n",
       "      <td>3.05</td>\n",
       "      <td>北京市</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.39</td>\n",
       "      <td>1.22</td>\n",
       "      <td>2.03</td>\n",
       "      <td>2.07</td>\n",
       "      <td>2.24</td>\n",
       "      <td>2.38</td>\n",
       "      <td>...</td>\n",
       "      <td>1.13</td>\n",
       "      <td>1.12</td>\n",
       "      <td>1.17</td>\n",
       "      <td>1.48</td>\n",
       "      <td>1.63</td>\n",
       "      <td>1.85</td>\n",
       "      <td>2.01</td>\n",
       "      <td>1.86</td>\n",
       "      <td>1.41</td>\n",
       "      <td>1.50</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 62 columns</p>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "execution_count": 6
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "source": [
    "od_col = ['o_province', 'd_province']\r\n",
    "od_df = pd.DataFrame(d_beijing, columns=od_col)\r\n",
    "od_df"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "   o_province d_province\n",
       "0         河北省        北京市\n",
       "1         天津市        北京市\n",
       "2         山东省        北京市\n",
       "3         河南省        北京市\n",
       "4         广东省        北京市\n",
       "5         江苏省        北京市\n",
       "6         山西省        北京市\n",
       "7      内蒙古自治区        北京市\n",
       "8         上海市        北京市\n",
       "9         浙江省        北京市\n",
       "10       黑龙江省        北京市\n",
       "11        辽宁省        北京市\n",
       "12        海南省        北京市\n",
       "13        安徽省        北京市\n",
       "14        陕西省        北京市\n",
       "15        湖北省        北京市\n",
       "16        四川省        北京市\n",
       "17        吉林省        北京市\n",
       "18        湖南省        北京市\n",
       "19        福建省        北京市\n",
       "20        云南省        北京市\n",
       "21        重庆市        北京市\n",
       "22        江西省        北京市\n",
       "23    广西壮族自治区        北京市\n",
       "24        甘肃省        北京市\n",
       "25   新疆维吾尔自治区        北京市\n",
       "26        贵州省        北京市\n",
       "27    宁夏回族自治区        北京市\n",
       "28        青海省        北京市"
      ],
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>o_province</th>\n",
       "      <th>d_province</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>河北省</td>\n",
       "      <td>北京市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>天津市</td>\n",
       "      <td>北京市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>山东省</td>\n",
       "      <td>北京市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>河南省</td>\n",
       "      <td>北京市</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>广东省</td>\n",
       "      <td>北京市</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>北京市</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>山西省</td>\n",
       "      <td>北京市</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>北京市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>上海市</td>\n",
       "      <td>北京市</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>北京市</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>北京市</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>北京市</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>海南省</td>\n",
       "      <td>北京市</td>\n",
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       "      <th>13</th>\n",
       "      <td>安徽省</td>\n",
       "      <td>北京市</td>\n",
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       "      <th>14</th>\n",
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       "      <td>北京市</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
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       "      <td>北京市</td>\n",
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       "    <tr>\n",
       "      <th>16</th>\n",
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       "      <td>北京市</td>\n",
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       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>吉林省</td>\n",
       "      <td>北京市</td>\n",
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       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>湖南省</td>\n",
       "      <td>北京市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>福建省</td>\n",
       "      <td>北京市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>云南省</td>\n",
       "      <td>北京市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>北京市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>江西省</td>\n",
       "      <td>北京市</td>\n",
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       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>北京市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>北京市</td>\n",
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       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>北京市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>贵州省</td>\n",
       "      <td>北京市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>北京市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>青海省</td>\n",
       "      <td>北京市</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "execution_count": 15
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "source": [
    "o_list = od_df['o_province'].to_list()"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "source": [
    "move_df = d_beijing.drop(od_col, axis=1)\r\n",
    "move_df.pct_change(axis=1).head()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
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       "<p>5 rows × 60 columns</p>\n",
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     },
     "metadata": {},
     "execution_count": 18
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "source": [
    "re_move_df = move_df.T\r\n",
    "re_move_df.columns = o_list\r\n",
    "re_move_df"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "              河北省    天津市   山东省    河南省   广东省   江苏省   山西省  内蒙古自治区   上海市   浙江省  \\\n",
       "2021-01-01  46.77   9.49  5.62   4.10  3.05  2.86  2.85    2.56  2.53  1.81   \n",
       "2021-01-02  57.55   7.68  4.83   3.82  1.82  1.73  2.69    2.45  1.22  1.08   \n",
       "2021-01-03  61.18   8.09  5.04   3.65  1.39  1.45  3.16    2.41  0.90  0.76   \n",
       "2021-01-04  59.34   9.56  5.77   4.28  1.22  1.90  3.11    2.13  1.14  0.84   \n",
       "2021-01-05  47.15   7.14  6.89   5.96  2.03  2.87  3.59    2.91  1.46  1.34   \n",
       "2021-01-06  47.10   6.55  6.97   5.77  2.07  2.80  3.75    3.34  1.65  1.44   \n",
       "2021-01-07  49.12   7.32  6.00   4.96  2.24  2.82  3.09    3.08  1.91  1.46   \n",
       "2021-01-08  48.71   9.25  5.45   4.48  2.38  2.64  2.84    2.91  2.12  1.53   \n",
       "2021-01-09  42.81  10.21  6.32   4.46  3.08  2.80  2.84    3.11  2.86  1.96   \n",
       "2021-01-10  45.65   9.06  6.31   4.37  2.76  2.46  2.78    3.22  2.15  1.61   \n",
       "2021-01-11  48.84  13.64  5.55   3.61  2.17  2.42  2.42    2.58  2.08  1.39   \n",
       "2021-01-12  48.20   9.70  6.43   3.46  2.46  2.67  2.64    2.77  2.34  1.52   \n",
       "2021-01-13  30.24  11.75  8.28   4.76  3.56  3.80  3.21    3.80  3.53  2.14   \n",
       "2021-01-14  25.68  14.35  7.83   4.94  3.76  3.82  3.27    3.88  3.92  2.28   \n",
       "2021-01-15  24.01  14.70  7.90   4.90  4.38  3.99  2.95    3.54  4.13  2.58   \n",
       "2021-01-16  20.40  15.25  7.82   4.12  5.00  4.36  2.84    3.37  5.08  3.07   \n",
       "2021-01-17  22.03  14.74  7.94   4.76  4.39  3.91  3.28    3.94  3.95  2.67   \n",
       "2021-01-18  19.24  24.48  7.96   4.23  3.88  3.75  3.07    3.47  3.73  2.46   \n",
       "2021-01-19  40.79  11.96  6.42   3.59  3.23  2.96  2.44    2.92  3.09  2.05   \n",
       "2021-01-20  44.59   9.90  5.71   3.13  3.21  3.04  2.53    2.76  2.93  1.88   \n",
       "2021-01-21  44.70   9.51  5.38   3.33  3.36  2.95  2.47    2.87  3.10  1.91   \n",
       "2021-01-22  45.25  11.33  5.21   3.08  3.47  2.94  2.07    2.77  3.21  1.94   \n",
       "2021-01-23  38.12  11.78  6.23   3.57  4.45  3.25  2.14    2.70  4.26  2.38   \n",
       "2021-01-24  39.31  11.52  6.29   3.66  3.60  2.84  2.90    3.18  2.99  1.99   \n",
       "2021-01-25  50.67  15.96  4.54   2.55  2.33  2.05  2.01    2.14  2.08  1.39   \n",
       "2021-01-26  47.76  11.03  5.04   2.90  2.86  2.66  2.36    3.03  2.37  1.60   \n",
       "2021-01-27  45.28  10.39  5.95   3.51  3.12  2.60  2.55    2.84  2.49  1.83   \n",
       "2021-01-28  49.05   9.47  5.20   3.25  2.94  2.56  2.19    2.53  2.31  1.80   \n",
       "2021-01-29  50.38   9.80  5.16   3.08  3.09  2.63  2.02    2.47  2.17  1.43   \n",
       "2021-01-30  44.41  10.79  5.70   3.36  3.76  2.68  2.35    2.69  2.62  2.03   \n",
       "2021-01-31  45.06   8.97  6.25   3.64  3.57  2.67  2.65    3.19  2.21  1.80   \n",
       "2021-02-01  58.34  11.51  3.89   2.36  2.19  1.78  1.70    1.94  1.52  1.17   \n",
       "2021-02-02  52.18  11.55  4.79   2.79  2.53  2.00  2.06    2.52  1.64  1.20   \n",
       "2021-02-03  50.06   9.92  4.72   3.29  2.86  2.35  2.20    2.78  1.91  1.59   \n",
       "2021-02-04  54.42   9.01  4.45   3.21  2.60  2.07  2.10    2.22  1.75  1.39   \n",
       "2021-02-05  51.42   9.52  4.61   3.06  2.87  2.21  2.03    2.49  1.98  1.63   \n",
       "2021-02-06  44.71   9.59  5.00   3.62  4.02  2.55  2.36    2.77  2.61  1.85   \n",
       "2021-02-07  54.08   9.67  4.11   2.87  2.67  1.85  2.09    2.34  1.66  1.42   \n",
       "2021-02-08  50.01   9.26  4.59   3.29  3.10  2.23  2.56    2.62  1.96  1.59   \n",
       "2021-02-09  46.27   8.93  4.94   3.38  3.43  2.45  2.63    2.72  2.15  1.87   \n",
       "2021-02-10  47.16   9.19  4.71   3.25  2.95  2.30  2.73    2.70  2.21  1.53   \n",
       "2021-02-11  46.25   9.19  4.98   3.22  2.82  2.00  2.87    2.50  2.03  1.44   \n",
       "2021-02-12  54.87   8.07  3.81   2.60  1.98  1.27  2.41    2.22  1.32  0.73   \n",
       "2021-02-13  59.96   7.26  4.17   2.23  1.07  1.11  2.14    2.37  0.70  0.64   \n",
       "2021-02-14  54.01   7.48  6.29   3.79  1.11  1.28  2.91    2.84  0.63  0.56   \n",
       "2021-02-15  51.72   6.40  7.23   5.05  0.96  1.36  3.62    3.16  0.51  0.59   \n",
       "2021-02-16  47.23   5.41  8.27   6.98  0.93  1.34  4.67    3.34  0.50  0.60   \n",
       "2021-02-17  43.85   4.62  8.54   9.04  0.88  1.49  5.96    3.72  0.43  0.62   \n",
       "2021-02-18  43.60   5.16  8.64  10.33  0.80  1.71  5.66    3.51  0.44  0.60   \n",
       "2021-02-19  43.73   4.44  8.23   8.90  1.01  1.69  6.15    3.51  0.56  0.72   \n",
       "2021-02-20  40.53   4.01  8.27  10.46  1.13  1.83  6.05    3.39  0.62  0.74   \n",
       "2021-02-21  38.93   3.96  8.65  11.28  1.12  2.01  5.95    3.49  0.63  0.87   \n",
       "2021-02-22  43.07   5.78  7.15   9.52  1.17  2.18  4.89    3.05  0.88  0.84   \n",
       "2021-02-23  40.48   5.05  7.10   9.01  1.48  2.46  5.01    3.32  1.18  1.05   \n",
       "2021-02-24  38.29   4.62  7.21   9.55  1.63  2.74  4.67    3.32  1.47  1.16   \n",
       "2021-02-25  42.86   5.12  6.23   6.86  1.85  2.74  3.96    3.18  1.61  1.25   \n",
       "2021-02-26  40.57   5.96  5.60   6.46  2.01  2.76  4.00    3.41  2.03  1.57   \n",
       "2021-02-27  44.45   5.39  6.86   6.39  1.86  2.44  4.22    3.56  1.44  1.31   \n",
       "2021-02-28  36.85   3.81  8.45  12.15  1.41  3.02  4.26    2.78  0.86  1.06   \n",
       "2021-03-01  45.94   6.53  6.97   7.89  1.50  2.40  3.56    2.57  1.10  1.02   \n",
       "\n",
       "            ...   福建省   云南省   重庆市   江西省  广西壮族自治区   甘肃省  新疆维吾尔自治区   贵州省  \\\n",
       "2021-01-01  ...  0.92  0.83  0.78  0.70     0.52  0.48      0.44  0.41   \n",
       "2021-01-02  ...  0.68  0.68  0.53  0.46     0.38  0.42      0.39  0.29   \n",
       "2021-01-03  ...  0.52  0.48  0.42  0.45     0.33  0.35      0.22  0.21   \n",
       "2021-01-04  ...  0.41  0.35  0.39  0.43     0.22  0.26      0.15  0.17   \n",
       "2021-01-05  ...  0.67  0.71  0.61  0.70     0.43  0.49      0.49  0.34   \n",
       "2021-01-06  ...  0.64  0.63  0.62  0.69     0.41  0.56      0.37  0.31   \n",
       "2021-01-07  ...  0.72  0.69  0.66  0.63     0.46  0.55      0.37  0.31   \n",
       "2021-01-08  ...  0.70  0.58  0.72  0.67     0.41  0.59      0.50  0.34   \n",
       "2021-01-09  ...  0.80  0.71  0.68  0.74     0.57  0.72      0.62  0.44   \n",
       "2021-01-10  ...  0.75  0.78  0.70  0.72     0.53  0.73      0.58  0.46   \n",
       "2021-01-11  ...  0.58  0.57  0.71  0.57     0.36  0.48      0.51  0.29   \n",
       "2021-01-12  ...  0.61  0.73  0.74  0.72     0.46  0.54      0.75  0.33   \n",
       "2021-01-13  ...  0.85  0.90  1.01  1.01     0.58  0.81      1.05  0.41   \n",
       "2021-01-14  ...  1.18  0.95  1.05  1.00     0.88  0.82      1.05  0.54   \n",
       "2021-01-15  ...  1.04  1.15  1.17  0.96     0.90  0.85      0.97  0.48   \n",
       "2021-01-16  ...  1.38  1.16  1.26  1.09     1.20  0.72      1.02  0.49   \n",
       "2021-01-17  ...  1.19  1.18  1.10  1.19     0.95  0.83      1.26  0.45   \n",
       "2021-01-18  ...  0.92  0.93  1.07  0.86     0.81  0.61      0.99  0.36   \n",
       "2021-01-19  ...  0.91  0.76  0.90  0.65     0.58  0.59      0.95  0.37   \n",
       "2021-01-20  ...  0.77  0.79  0.97  0.84     0.55  0.48      1.26  0.37   \n",
       "2021-01-21  ...  0.81  0.70  0.87  0.75     0.56  0.57      1.22  0.38   \n",
       "2021-01-22  ...  0.71  0.75  0.85  0.75     0.56  0.44      1.03  0.30   \n",
       "2021-01-23  ...  0.80  0.79  1.02  0.81     0.55  0.62      1.13  0.46   \n",
       "2021-01-24  ...  0.66  0.92  0.81  0.75     0.49  0.56      1.09  0.42   \n",
       "2021-01-25  ...  0.49  0.50  0.63  0.41     0.29  0.40      0.76  0.26   \n",
       "2021-01-26  ...  0.68  0.64  0.74  0.60     0.49  0.49      1.12  0.29   \n",
       "2021-01-27  ...  0.70  0.71  0.81  0.58     0.42  0.49      1.04  0.35   \n",
       "2021-01-28  ...  0.69  0.56  0.81  0.65     0.48  0.63      0.92  0.37   \n",
       "2021-01-29  ...  0.52  0.72  0.71  0.57     0.51  0.48      1.08  0.30   \n",
       "2021-01-30  ...  0.66  0.70  0.74  0.61     0.48  0.56      1.21  0.38   \n",
       "2021-01-31  ...  0.82  0.80  0.86  0.70     0.72  0.53      0.29  0.39   \n",
       "2021-02-01  ...  0.38  0.56  0.47  0.52     0.32  0.34      0.74  0.25   \n",
       "2021-02-02  ...  0.52  0.51  0.50  0.53     0.43  0.39      1.23  0.35   \n",
       "2021-02-03  ...  0.51  0.56  0.61  0.64     0.46  0.47      1.18  0.33   \n",
       "2021-02-04  ...  0.56  0.60  0.55  0.59     0.43  0.45      0.92  0.36   \n",
       "2021-02-05  ...  0.60  0.64  0.61  0.66     0.48  0.52      1.06  0.36   \n",
       "2021-02-06  ...  0.84  0.73  0.80  0.74     0.66  0.50      0.94  0.57   \n",
       "2021-02-07  ...  0.52  0.60  0.58  0.63     0.52  0.49      1.15  0.40   \n",
       "2021-02-08  ...  0.59  0.57  0.67  0.60     0.48  0.50      0.91  0.44   \n",
       "2021-02-09  ...  0.68  0.69  0.66  0.71     0.52  0.56      1.05  0.44   \n",
       "2021-02-10  ...  0.63  0.58  0.72  0.65     0.44  0.51      1.03  0.43   \n",
       "2021-02-11  ...  0.49  0.53  0.48  0.73     0.50  0.61      1.19  0.34   \n",
       "2021-02-12  ...  0.39  0.48  0.47  0.42     0.35  0.56      2.01  0.29   \n",
       "2021-02-13  ...  0.29  0.30  0.26  0.46     0.32  0.30      1.48  0.26   \n",
       "2021-02-14  ...  0.38  0.44  0.37  0.50     0.23  0.46      0.87  0.26   \n",
       "2021-02-15  ...  0.43  0.47  0.55  0.64     0.27  0.49      0.66  0.26   \n",
       "2021-02-16  ...  0.45  0.42  0.59  0.87     0.32  0.68      0.43  0.30   \n",
       "2021-02-17  ...  0.52  0.37  0.51  0.97     0.27  0.88      0.30  0.24   \n",
       "2021-02-18  ...  0.52  0.26  0.56  0.85     0.25  0.81      0.19  0.22   \n",
       "2021-02-19  ...  0.64  0.38  0.56  0.98     0.29  0.92      0.32  0.26   \n",
       "2021-02-20  ...  0.65  0.39  0.74  1.03     0.34  0.99      0.34  0.28   \n",
       "2021-02-21  ...  0.67  0.41  0.78  1.07     0.33  1.06      0.30  0.29   \n",
       "2021-02-22  ...  0.69  0.36  0.70  0.94     0.26  0.93      0.26  0.26   \n",
       "2021-02-23  ...  0.83  0.47  0.68  1.01     0.35  0.95      0.45  0.38   \n",
       "2021-02-24  ...  0.86  0.46  0.82  1.20     0.35  1.12      0.52  0.37   \n",
       "2021-02-25  ...  0.89  0.49  0.85  1.05     0.36  0.96      0.55  0.38   \n",
       "2021-02-26  ...  0.96  0.56  0.85  0.97     0.43  1.10      0.66  0.42   \n",
       "2021-02-27  ...  0.79  0.48  0.71  0.74     0.37  0.83      0.60  0.34   \n",
       "2021-02-28  ...  0.84  0.43  0.71  1.42     0.30  0.85      0.46  0.30   \n",
       "2021-03-01  ...  0.68  0.34  0.64  0.90     0.29  0.65      0.44  0.30   \n",
       "\n",
       "            宁夏回族自治区   青海省  \n",
       "2021-01-01     0.23  0.16  \n",
       "2021-01-02     0.21  0.08  \n",
       "2021-01-03     0.17  0.08  \n",
       "2021-01-04     0.15  0.06  \n",
       "2021-01-05     0.18  0.08  \n",
       "2021-01-06     0.26  0.15  \n",
       "2021-01-07     0.26  0.12  \n",
       "2021-01-08     0.26  0.16  \n",
       "2021-01-09     0.25  0.16  \n",
       "2021-01-10     0.27  0.15  \n",
       "2021-01-11     0.16  0.11  \n",
       "2021-01-12     0.24  0.13  \n",
       "2021-01-13     0.30  0.16  \n",
       "2021-01-14     0.33  0.21  \n",
       "2021-01-15     0.42  0.25  \n",
       "2021-01-16     0.38  0.20  \n",
       "2021-01-17     0.38  0.23  \n",
       "2021-01-18     0.28  0.12  \n",
       "2021-01-19     0.27  0.15  \n",
       "2021-01-20     0.23  0.17  \n",
       "2021-01-21     0.25  0.19  \n",
       "2021-01-22     0.19  0.13  \n",
       "2021-01-23     0.35  0.15  \n",
       "2021-01-24     0.28  0.14  \n",
       "2021-01-25     0.17  0.09  \n",
       "2021-01-26     0.25  0.14  \n",
       "2021-01-27     0.27  0.18  \n",
       "2021-01-28     0.30  0.11  \n",
       "2021-01-29     0.26  0.13  \n",
       "2021-01-30     0.27  0.15  \n",
       "2021-01-31     0.30  0.23  \n",
       "2021-02-01     0.16  0.09  \n",
       "2021-02-02     0.19  0.13  \n",
       "2021-02-03     0.25  0.15  \n",
       "2021-02-04     0.29  0.15  \n",
       "2021-02-05     0.30  0.13  \n",
       "2021-02-06     0.32  0.19  \n",
       "2021-02-07     0.20  0.16  \n",
       "2021-02-08     0.28  0.18  \n",
       "2021-02-09     0.30  0.16  \n",
       "2021-02-10     0.29  0.17  \n",
       "2021-02-11     0.29  0.17  \n",
       "2021-02-12     0.18  0.09  \n",
       "2021-02-13     0.25  0.07  \n",
       "2021-02-14     0.18  0.09  \n",
       "2021-02-15     0.22  0.08  \n",
       "2021-02-16     0.24  0.09  \n",
       "2021-02-17     0.26  0.07  \n",
       "2021-02-18     0.23  0.07  \n",
       "2021-02-19     0.27  0.07  \n",
       "2021-02-20     0.28  0.08  \n",
       "2021-02-21     0.22  0.09  \n",
       "2021-02-22     0.26  0.09  \n",
       "2021-02-23     0.30  0.10  \n",
       "2021-02-24     0.28  0.11  \n",
       "2021-02-25     0.26  0.11  \n",
       "2021-02-26     0.29  0.13  \n",
       "2021-02-27     0.25  0.12  \n",
       "2021-02-28     0.20  0.12  \n",
       "2021-03-01     0.22  0.09  \n",
       "\n",
       "[60 rows x 29 columns]"
      ],
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>河北省</th>\n",
       "      <th>天津市</th>\n",
       "      <th>山东省</th>\n",
       "      <th>河南省</th>\n",
       "      <th>广东省</th>\n",
       "      <th>江苏省</th>\n",
       "      <th>山西省</th>\n",
       "      <th>内蒙古自治区</th>\n",
       "      <th>上海市</th>\n",
       "      <th>浙江省</th>\n",
       "      <th>...</th>\n",
       "      <th>福建省</th>\n",
       "      <th>云南省</th>\n",
       "      <th>重庆市</th>\n",
       "      <th>江西省</th>\n",
       "      <th>广西壮族自治区</th>\n",
       "      <th>甘肃省</th>\n",
       "      <th>新疆维吾尔自治区</th>\n",
       "      <th>贵州省</th>\n",
       "      <th>宁夏回族自治区</th>\n",
       "      <th>青海省</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-01-01</th>\n",
       "      <td>46.77</td>\n",
       "      <td>9.49</td>\n",
       "      <td>5.62</td>\n",
       "      <td>4.10</td>\n",
       "      <td>3.05</td>\n",
       "      <td>2.86</td>\n",
       "      <td>2.85</td>\n",
       "      <td>2.56</td>\n",
       "      <td>2.53</td>\n",
       "      <td>1.81</td>\n",
       "      <td>...</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.83</td>\n",
       "      <td>0.78</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-02</th>\n",
       "      <td>57.55</td>\n",
       "      <td>7.68</td>\n",
       "      <td>4.83</td>\n",
       "      <td>3.82</td>\n",
       "      <td>1.82</td>\n",
       "      <td>1.73</td>\n",
       "      <td>2.69</td>\n",
       "      <td>2.45</td>\n",
       "      <td>1.22</td>\n",
       "      <td>1.08</td>\n",
       "      <td>...</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-03</th>\n",
       "      <td>61.18</td>\n",
       "      <td>8.09</td>\n",
       "      <td>5.04</td>\n",
       "      <td>3.65</td>\n",
       "      <td>1.39</td>\n",
       "      <td>1.45</td>\n",
       "      <td>3.16</td>\n",
       "      <td>2.41</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.76</td>\n",
       "      <td>...</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-04</th>\n",
       "      <td>59.34</td>\n",
       "      <td>9.56</td>\n",
       "      <td>5.77</td>\n",
       "      <td>4.28</td>\n",
       "      <td>1.22</td>\n",
       "      <td>1.90</td>\n",
       "      <td>3.11</td>\n",
       "      <td>2.13</td>\n",
       "      <td>1.14</td>\n",
       "      <td>0.84</td>\n",
       "      <td>...</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-05</th>\n",
       "      <td>47.15</td>\n",
       "      <td>7.14</td>\n",
       "      <td>6.89</td>\n",
       "      <td>5.96</td>\n",
       "      <td>2.03</td>\n",
       "      <td>2.87</td>\n",
       "      <td>3.59</td>\n",
       "      <td>2.91</td>\n",
       "      <td>1.46</td>\n",
       "      <td>1.34</td>\n",
       "      <td>...</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-06</th>\n",
       "      <td>47.10</td>\n",
       "      <td>6.55</td>\n",
       "      <td>6.97</td>\n",
       "      <td>5.77</td>\n",
       "      <td>2.07</td>\n",
       "      <td>2.80</td>\n",
       "      <td>3.75</td>\n",
       "      <td>3.34</td>\n",
       "      <td>1.65</td>\n",
       "      <td>1.44</td>\n",
       "      <td>...</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.31</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-07</th>\n",
       "      <td>49.12</td>\n",
       "      <td>7.32</td>\n",
       "      <td>6.00</td>\n",
       "      <td>4.96</td>\n",
       "      <td>2.24</td>\n",
       "      <td>2.82</td>\n",
       "      <td>3.09</td>\n",
       "      <td>3.08</td>\n",
       "      <td>1.91</td>\n",
       "      <td>1.46</td>\n",
       "      <td>...</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.55</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.31</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-08</th>\n",
       "      <td>48.71</td>\n",
       "      <td>9.25</td>\n",
       "      <td>5.45</td>\n",
       "      <td>4.48</td>\n",
       "      <td>2.38</td>\n",
       "      <td>2.64</td>\n",
       "      <td>2.84</td>\n",
       "      <td>2.91</td>\n",
       "      <td>2.12</td>\n",
       "      <td>1.53</td>\n",
       "      <td>...</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.59</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-09</th>\n",
       "      <td>42.81</td>\n",
       "      <td>10.21</td>\n",
       "      <td>6.32</td>\n",
       "      <td>4.46</td>\n",
       "      <td>3.08</td>\n",
       "      <td>2.80</td>\n",
       "      <td>2.84</td>\n",
       "      <td>3.11</td>\n",
       "      <td>2.86</td>\n",
       "      <td>1.96</td>\n",
       "      <td>...</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-10</th>\n",
       "      <td>45.65</td>\n",
       "      <td>9.06</td>\n",
       "      <td>6.31</td>\n",
       "      <td>4.37</td>\n",
       "      <td>2.76</td>\n",
       "      <td>2.46</td>\n",
       "      <td>2.78</td>\n",
       "      <td>3.22</td>\n",
       "      <td>2.15</td>\n",
       "      <td>1.61</td>\n",
       "      <td>...</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.78</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.73</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-11</th>\n",
       "      <td>48.84</td>\n",
       "      <td>13.64</td>\n",
       "      <td>5.55</td>\n",
       "      <td>3.61</td>\n",
       "      <td>2.17</td>\n",
       "      <td>2.42</td>\n",
       "      <td>2.42</td>\n",
       "      <td>2.58</td>\n",
       "      <td>2.08</td>\n",
       "      <td>1.39</td>\n",
       "      <td>...</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-12</th>\n",
       "      <td>48.20</td>\n",
       "      <td>9.70</td>\n",
       "      <td>6.43</td>\n",
       "      <td>3.46</td>\n",
       "      <td>2.46</td>\n",
       "      <td>2.67</td>\n",
       "      <td>2.64</td>\n",
       "      <td>2.77</td>\n",
       "      <td>2.34</td>\n",
       "      <td>1.52</td>\n",
       "      <td>...</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.73</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.54</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.24</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-13</th>\n",
       "      <td>30.24</td>\n",
       "      <td>11.75</td>\n",
       "      <td>8.28</td>\n",
       "      <td>4.76</td>\n",
       "      <td>3.56</td>\n",
       "      <td>3.80</td>\n",
       "      <td>3.21</td>\n",
       "      <td>3.80</td>\n",
       "      <td>3.53</td>\n",
       "      <td>2.14</td>\n",
       "      <td>...</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.90</td>\n",
       "      <td>1.01</td>\n",
       "      <td>1.01</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.81</td>\n",
       "      <td>1.05</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-14</th>\n",
       "      <td>25.68</td>\n",
       "      <td>14.35</td>\n",
       "      <td>7.83</td>\n",
       "      <td>4.94</td>\n",
       "      <td>3.76</td>\n",
       "      <td>3.82</td>\n",
       "      <td>3.27</td>\n",
       "      <td>3.88</td>\n",
       "      <td>3.92</td>\n",
       "      <td>2.28</td>\n",
       "      <td>...</td>\n",
       "      <td>1.18</td>\n",
       "      <td>0.95</td>\n",
       "      <td>1.05</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.82</td>\n",
       "      <td>1.05</td>\n",
       "      <td>0.54</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-15</th>\n",
       "      <td>24.01</td>\n",
       "      <td>14.70</td>\n",
       "      <td>7.90</td>\n",
       "      <td>4.90</td>\n",
       "      <td>4.38</td>\n",
       "      <td>3.99</td>\n",
       "      <td>2.95</td>\n",
       "      <td>3.54</td>\n",
       "      <td>4.13</td>\n",
       "      <td>2.58</td>\n",
       "      <td>...</td>\n",
       "      <td>1.04</td>\n",
       "      <td>1.15</td>\n",
       "      <td>1.17</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-16</th>\n",
       "      <td>20.40</td>\n",
       "      <td>15.25</td>\n",
       "      <td>7.82</td>\n",
       "      <td>4.12</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.36</td>\n",
       "      <td>2.84</td>\n",
       "      <td>3.37</td>\n",
       "      <td>5.08</td>\n",
       "      <td>3.07</td>\n",
       "      <td>...</td>\n",
       "      <td>1.38</td>\n",
       "      <td>1.16</td>\n",
       "      <td>1.26</td>\n",
       "      <td>1.09</td>\n",
       "      <td>1.20</td>\n",
       "      <td>0.72</td>\n",
       "      <td>1.02</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-17</th>\n",
       "      <td>22.03</td>\n",
       "      <td>14.74</td>\n",
       "      <td>7.94</td>\n",
       "      <td>4.76</td>\n",
       "      <td>4.39</td>\n",
       "      <td>3.91</td>\n",
       "      <td>3.28</td>\n",
       "      <td>3.94</td>\n",
       "      <td>3.95</td>\n",
       "      <td>2.67</td>\n",
       "      <td>...</td>\n",
       "      <td>1.19</td>\n",
       "      <td>1.18</td>\n",
       "      <td>1.10</td>\n",
       "      <td>1.19</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.83</td>\n",
       "      <td>1.26</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-18</th>\n",
       "      <td>19.24</td>\n",
       "      <td>24.48</td>\n",
       "      <td>7.96</td>\n",
       "      <td>4.23</td>\n",
       "      <td>3.88</td>\n",
       "      <td>3.75</td>\n",
       "      <td>3.07</td>\n",
       "      <td>3.47</td>\n",
       "      <td>3.73</td>\n",
       "      <td>2.46</td>\n",
       "      <td>...</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1.07</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-19</th>\n",
       "      <td>40.79</td>\n",
       "      <td>11.96</td>\n",
       "      <td>6.42</td>\n",
       "      <td>3.59</td>\n",
       "      <td>3.23</td>\n",
       "      <td>2.96</td>\n",
       "      <td>2.44</td>\n",
       "      <td>2.92</td>\n",
       "      <td>3.09</td>\n",
       "      <td>2.05</td>\n",
       "      <td>...</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.59</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-20</th>\n",
       "      <td>44.59</td>\n",
       "      <td>9.90</td>\n",
       "      <td>5.71</td>\n",
       "      <td>3.13</td>\n",
       "      <td>3.21</td>\n",
       "      <td>3.04</td>\n",
       "      <td>2.53</td>\n",
       "      <td>2.76</td>\n",
       "      <td>2.93</td>\n",
       "      <td>1.88</td>\n",
       "      <td>...</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0.79</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.84</td>\n",
       "      <td>0.55</td>\n",
       "      <td>0.48</td>\n",
       "      <td>1.26</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-21</th>\n",
       "      <td>44.70</td>\n",
       "      <td>9.51</td>\n",
       "      <td>5.38</td>\n",
       "      <td>3.33</td>\n",
       "      <td>3.36</td>\n",
       "      <td>2.95</td>\n",
       "      <td>2.47</td>\n",
       "      <td>2.87</td>\n",
       "      <td>3.10</td>\n",
       "      <td>1.91</td>\n",
       "      <td>...</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.87</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.57</td>\n",
       "      <td>1.22</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-22</th>\n",
       "      <td>45.25</td>\n",
       "      <td>11.33</td>\n",
       "      <td>5.21</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.47</td>\n",
       "      <td>2.94</td>\n",
       "      <td>2.07</td>\n",
       "      <td>2.77</td>\n",
       "      <td>3.21</td>\n",
       "      <td>1.94</td>\n",
       "      <td>...</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.44</td>\n",
       "      <td>1.03</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-23</th>\n",
       "      <td>38.12</td>\n",
       "      <td>11.78</td>\n",
       "      <td>6.23</td>\n",
       "      <td>3.57</td>\n",
       "      <td>4.45</td>\n",
       "      <td>3.25</td>\n",
       "      <td>2.14</td>\n",
       "      <td>2.70</td>\n",
       "      <td>4.26</td>\n",
       "      <td>2.38</td>\n",
       "      <td>...</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.79</td>\n",
       "      <td>1.02</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.55</td>\n",
       "      <td>0.62</td>\n",
       "      <td>1.13</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-24</th>\n",
       "      <td>39.31</td>\n",
       "      <td>11.52</td>\n",
       "      <td>6.29</td>\n",
       "      <td>3.66</td>\n",
       "      <td>3.60</td>\n",
       "      <td>2.84</td>\n",
       "      <td>2.90</td>\n",
       "      <td>3.18</td>\n",
       "      <td>2.99</td>\n",
       "      <td>1.99</td>\n",
       "      <td>...</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.56</td>\n",
       "      <td>1.09</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-25</th>\n",
       "      <td>50.67</td>\n",
       "      <td>15.96</td>\n",
       "      <td>4.54</td>\n",
       "      <td>2.55</td>\n",
       "      <td>2.33</td>\n",
       "      <td>2.05</td>\n",
       "      <td>2.01</td>\n",
       "      <td>2.14</td>\n",
       "      <td>2.08</td>\n",
       "      <td>1.39</td>\n",
       "      <td>...</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-26</th>\n",
       "      <td>47.76</td>\n",
       "      <td>11.03</td>\n",
       "      <td>5.04</td>\n",
       "      <td>2.90</td>\n",
       "      <td>2.86</td>\n",
       "      <td>2.66</td>\n",
       "      <td>2.36</td>\n",
       "      <td>3.03</td>\n",
       "      <td>2.37</td>\n",
       "      <td>1.60</td>\n",
       "      <td>...</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.49</td>\n",
       "      <td>1.12</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-27</th>\n",
       "      <td>45.28</td>\n",
       "      <td>10.39</td>\n",
       "      <td>5.95</td>\n",
       "      <td>3.51</td>\n",
       "      <td>3.12</td>\n",
       "      <td>2.60</td>\n",
       "      <td>2.55</td>\n",
       "      <td>2.84</td>\n",
       "      <td>2.49</td>\n",
       "      <td>1.83</td>\n",
       "      <td>...</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.49</td>\n",
       "      <td>1.04</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-28</th>\n",
       "      <td>49.05</td>\n",
       "      <td>9.47</td>\n",
       "      <td>5.20</td>\n",
       "      <td>3.25</td>\n",
       "      <td>2.94</td>\n",
       "      <td>2.56</td>\n",
       "      <td>2.19</td>\n",
       "      <td>2.53</td>\n",
       "      <td>2.31</td>\n",
       "      <td>1.80</td>\n",
       "      <td>...</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-29</th>\n",
       "      <td>50.38</td>\n",
       "      <td>9.80</td>\n",
       "      <td>5.16</td>\n",
       "      <td>3.08</td>\n",
       "      <td>3.09</td>\n",
       "      <td>2.63</td>\n",
       "      <td>2.02</td>\n",
       "      <td>2.47</td>\n",
       "      <td>2.17</td>\n",
       "      <td>1.43</td>\n",
       "      <td>...</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.48</td>\n",
       "      <td>1.08</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-30</th>\n",
       "      <td>44.41</td>\n",
       "      <td>10.79</td>\n",
       "      <td>5.70</td>\n",
       "      <td>3.36</td>\n",
       "      <td>3.76</td>\n",
       "      <td>2.68</td>\n",
       "      <td>2.35</td>\n",
       "      <td>2.69</td>\n",
       "      <td>2.62</td>\n",
       "      <td>2.03</td>\n",
       "      <td>...</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.56</td>\n",
       "      <td>1.21</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-31</th>\n",
       "      <td>45.06</td>\n",
       "      <td>8.97</td>\n",
       "      <td>6.25</td>\n",
       "      <td>3.64</td>\n",
       "      <td>3.57</td>\n",
       "      <td>2.67</td>\n",
       "      <td>2.65</td>\n",
       "      <td>3.19</td>\n",
       "      <td>2.21</td>\n",
       "      <td>1.80</td>\n",
       "      <td>...</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-01</th>\n",
       "      <td>58.34</td>\n",
       "      <td>11.51</td>\n",
       "      <td>3.89</td>\n",
       "      <td>2.36</td>\n",
       "      <td>2.19</td>\n",
       "      <td>1.78</td>\n",
       "      <td>1.70</td>\n",
       "      <td>1.94</td>\n",
       "      <td>1.52</td>\n",
       "      <td>1.17</td>\n",
       "      <td>...</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.47</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-02</th>\n",
       "      <td>52.18</td>\n",
       "      <td>11.55</td>\n",
       "      <td>4.79</td>\n",
       "      <td>2.79</td>\n",
       "      <td>2.53</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.06</td>\n",
       "      <td>2.52</td>\n",
       "      <td>1.64</td>\n",
       "      <td>1.20</td>\n",
       "      <td>...</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.39</td>\n",
       "      <td>1.23</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-03</th>\n",
       "      <td>50.06</td>\n",
       "      <td>9.92</td>\n",
       "      <td>4.72</td>\n",
       "      <td>3.29</td>\n",
       "      <td>2.86</td>\n",
       "      <td>2.35</td>\n",
       "      <td>2.20</td>\n",
       "      <td>2.78</td>\n",
       "      <td>1.91</td>\n",
       "      <td>1.59</td>\n",
       "      <td>...</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.47</td>\n",
       "      <td>1.18</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-04</th>\n",
       "      <td>54.42</td>\n",
       "      <td>9.01</td>\n",
       "      <td>4.45</td>\n",
       "      <td>3.21</td>\n",
       "      <td>2.60</td>\n",
       "      <td>2.07</td>\n",
       "      <td>2.10</td>\n",
       "      <td>2.22</td>\n",
       "      <td>1.75</td>\n",
       "      <td>1.39</td>\n",
       "      <td>...</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.55</td>\n",
       "      <td>0.59</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-05</th>\n",
       "      <td>51.42</td>\n",
       "      <td>9.52</td>\n",
       "      <td>4.61</td>\n",
       "      <td>3.06</td>\n",
       "      <td>2.87</td>\n",
       "      <td>2.21</td>\n",
       "      <td>2.03</td>\n",
       "      <td>2.49</td>\n",
       "      <td>1.98</td>\n",
       "      <td>1.63</td>\n",
       "      <td>...</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.52</td>\n",
       "      <td>1.06</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-06</th>\n",
       "      <td>44.71</td>\n",
       "      <td>9.59</td>\n",
       "      <td>5.00</td>\n",
       "      <td>3.62</td>\n",
       "      <td>4.02</td>\n",
       "      <td>2.55</td>\n",
       "      <td>2.36</td>\n",
       "      <td>2.77</td>\n",
       "      <td>2.61</td>\n",
       "      <td>1.85</td>\n",
       "      <td>...</td>\n",
       "      <td>0.84</td>\n",
       "      <td>0.73</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-07</th>\n",
       "      <td>54.08</td>\n",
       "      <td>9.67</td>\n",
       "      <td>4.11</td>\n",
       "      <td>2.87</td>\n",
       "      <td>2.67</td>\n",
       "      <td>1.85</td>\n",
       "      <td>2.09</td>\n",
       "      <td>2.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>1.42</td>\n",
       "      <td>...</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.49</td>\n",
       "      <td>1.15</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-08</th>\n",
       "      <td>50.01</td>\n",
       "      <td>9.26</td>\n",
       "      <td>4.59</td>\n",
       "      <td>3.29</td>\n",
       "      <td>3.10</td>\n",
       "      <td>2.23</td>\n",
       "      <td>2.56</td>\n",
       "      <td>2.62</td>\n",
       "      <td>1.96</td>\n",
       "      <td>1.59</td>\n",
       "      <td>...</td>\n",
       "      <td>0.59</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.91</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-09</th>\n",
       "      <td>46.27</td>\n",
       "      <td>8.93</td>\n",
       "      <td>4.94</td>\n",
       "      <td>3.38</td>\n",
       "      <td>3.43</td>\n",
       "      <td>2.45</td>\n",
       "      <td>2.63</td>\n",
       "      <td>2.72</td>\n",
       "      <td>2.15</td>\n",
       "      <td>1.87</td>\n",
       "      <td>...</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.56</td>\n",
       "      <td>1.05</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-10</th>\n",
       "      <td>47.16</td>\n",
       "      <td>9.19</td>\n",
       "      <td>4.71</td>\n",
       "      <td>3.25</td>\n",
       "      <td>2.95</td>\n",
       "      <td>2.30</td>\n",
       "      <td>2.73</td>\n",
       "      <td>2.70</td>\n",
       "      <td>2.21</td>\n",
       "      <td>1.53</td>\n",
       "      <td>...</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.51</td>\n",
       "      <td>1.03</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-11</th>\n",
       "      <td>46.25</td>\n",
       "      <td>9.19</td>\n",
       "      <td>4.98</td>\n",
       "      <td>3.22</td>\n",
       "      <td>2.82</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.87</td>\n",
       "      <td>2.50</td>\n",
       "      <td>2.03</td>\n",
       "      <td>1.44</td>\n",
       "      <td>...</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.73</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.61</td>\n",
       "      <td>1.19</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-12</th>\n",
       "      <td>54.87</td>\n",
       "      <td>8.07</td>\n",
       "      <td>3.81</td>\n",
       "      <td>2.60</td>\n",
       "      <td>1.98</td>\n",
       "      <td>1.27</td>\n",
       "      <td>2.41</td>\n",
       "      <td>2.22</td>\n",
       "      <td>1.32</td>\n",
       "      <td>0.73</td>\n",
       "      <td>...</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.47</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.56</td>\n",
       "      <td>2.01</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-13</th>\n",
       "      <td>59.96</td>\n",
       "      <td>7.26</td>\n",
       "      <td>4.17</td>\n",
       "      <td>2.23</td>\n",
       "      <td>1.07</td>\n",
       "      <td>1.11</td>\n",
       "      <td>2.14</td>\n",
       "      <td>2.37</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.64</td>\n",
       "      <td>...</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.30</td>\n",
       "      <td>1.48</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-14</th>\n",
       "      <td>54.01</td>\n",
       "      <td>7.48</td>\n",
       "      <td>6.29</td>\n",
       "      <td>3.79</td>\n",
       "      <td>1.11</td>\n",
       "      <td>1.28</td>\n",
       "      <td>2.91</td>\n",
       "      <td>2.84</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.56</td>\n",
       "      <td>...</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.87</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-15</th>\n",
       "      <td>51.72</td>\n",
       "      <td>6.40</td>\n",
       "      <td>7.23</td>\n",
       "      <td>5.05</td>\n",
       "      <td>0.96</td>\n",
       "      <td>1.36</td>\n",
       "      <td>3.62</td>\n",
       "      <td>3.16</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.59</td>\n",
       "      <td>...</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.47</td>\n",
       "      <td>0.55</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-16</th>\n",
       "      <td>47.23</td>\n",
       "      <td>5.41</td>\n",
       "      <td>8.27</td>\n",
       "      <td>6.98</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1.34</td>\n",
       "      <td>4.67</td>\n",
       "      <td>3.34</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.60</td>\n",
       "      <td>...</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.59</td>\n",
       "      <td>0.87</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.24</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-17</th>\n",
       "      <td>43.85</td>\n",
       "      <td>4.62</td>\n",
       "      <td>8.54</td>\n",
       "      <td>9.04</td>\n",
       "      <td>0.88</td>\n",
       "      <td>1.49</td>\n",
       "      <td>5.96</td>\n",
       "      <td>3.72</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.62</td>\n",
       "      <td>...</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.24</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-18</th>\n",
       "      <td>43.60</td>\n",
       "      <td>5.16</td>\n",
       "      <td>8.64</td>\n",
       "      <td>10.33</td>\n",
       "      <td>0.80</td>\n",
       "      <td>1.71</td>\n",
       "      <td>5.66</td>\n",
       "      <td>3.51</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.60</td>\n",
       "      <td>...</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-19</th>\n",
       "      <td>43.73</td>\n",
       "      <td>4.44</td>\n",
       "      <td>8.23</td>\n",
       "      <td>8.90</td>\n",
       "      <td>1.01</td>\n",
       "      <td>1.69</td>\n",
       "      <td>6.15</td>\n",
       "      <td>3.51</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.72</td>\n",
       "      <td>...</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-20</th>\n",
       "      <td>40.53</td>\n",
       "      <td>4.01</td>\n",
       "      <td>8.27</td>\n",
       "      <td>10.46</td>\n",
       "      <td>1.13</td>\n",
       "      <td>1.83</td>\n",
       "      <td>6.05</td>\n",
       "      <td>3.39</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.74</td>\n",
       "      <td>...</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.74</td>\n",
       "      <td>1.03</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-21</th>\n",
       "      <td>38.93</td>\n",
       "      <td>3.96</td>\n",
       "      <td>8.65</td>\n",
       "      <td>11.28</td>\n",
       "      <td>1.12</td>\n",
       "      <td>2.01</td>\n",
       "      <td>5.95</td>\n",
       "      <td>3.49</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.87</td>\n",
       "      <td>...</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.78</td>\n",
       "      <td>1.07</td>\n",
       "      <td>0.33</td>\n",
       "      <td>1.06</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-22</th>\n",
       "      <td>43.07</td>\n",
       "      <td>5.78</td>\n",
       "      <td>7.15</td>\n",
       "      <td>9.52</td>\n",
       "      <td>1.17</td>\n",
       "      <td>2.18</td>\n",
       "      <td>4.89</td>\n",
       "      <td>3.05</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.84</td>\n",
       "      <td>...</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-23</th>\n",
       "      <td>40.48</td>\n",
       "      <td>5.05</td>\n",
       "      <td>7.10</td>\n",
       "      <td>9.01</td>\n",
       "      <td>1.48</td>\n",
       "      <td>2.46</td>\n",
       "      <td>5.01</td>\n",
       "      <td>3.32</td>\n",
       "      <td>1.18</td>\n",
       "      <td>1.05</td>\n",
       "      <td>...</td>\n",
       "      <td>0.83</td>\n",
       "      <td>0.47</td>\n",
       "      <td>0.68</td>\n",
       "      <td>1.01</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-24</th>\n",
       "      <td>38.29</td>\n",
       "      <td>4.62</td>\n",
       "      <td>7.21</td>\n",
       "      <td>9.55</td>\n",
       "      <td>1.63</td>\n",
       "      <td>2.74</td>\n",
       "      <td>4.67</td>\n",
       "      <td>3.32</td>\n",
       "      <td>1.47</td>\n",
       "      <td>1.16</td>\n",
       "      <td>...</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.82</td>\n",
       "      <td>1.20</td>\n",
       "      <td>0.35</td>\n",
       "      <td>1.12</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-25</th>\n",
       "      <td>42.86</td>\n",
       "      <td>5.12</td>\n",
       "      <td>6.23</td>\n",
       "      <td>6.86</td>\n",
       "      <td>1.85</td>\n",
       "      <td>2.74</td>\n",
       "      <td>3.96</td>\n",
       "      <td>3.18</td>\n",
       "      <td>1.61</td>\n",
       "      <td>1.25</td>\n",
       "      <td>...</td>\n",
       "      <td>0.89</td>\n",
       "      <td>0.49</td>\n",
       "      <td>0.85</td>\n",
       "      <td>1.05</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.55</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-26</th>\n",
       "      <td>40.57</td>\n",
       "      <td>5.96</td>\n",
       "      <td>5.60</td>\n",
       "      <td>6.46</td>\n",
       "      <td>2.01</td>\n",
       "      <td>2.76</td>\n",
       "      <td>4.00</td>\n",
       "      <td>3.41</td>\n",
       "      <td>2.03</td>\n",
       "      <td>1.57</td>\n",
       "      <td>...</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.43</td>\n",
       "      <td>1.10</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-27</th>\n",
       "      <td>44.45</td>\n",
       "      <td>5.39</td>\n",
       "      <td>6.86</td>\n",
       "      <td>6.39</td>\n",
       "      <td>1.86</td>\n",
       "      <td>2.44</td>\n",
       "      <td>4.22</td>\n",
       "      <td>3.56</td>\n",
       "      <td>1.44</td>\n",
       "      <td>1.31</td>\n",
       "      <td>...</td>\n",
       "      <td>0.79</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.83</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-28</th>\n",
       "      <td>36.85</td>\n",
       "      <td>3.81</td>\n",
       "      <td>8.45</td>\n",
       "      <td>12.15</td>\n",
       "      <td>1.41</td>\n",
       "      <td>3.02</td>\n",
       "      <td>4.26</td>\n",
       "      <td>2.78</td>\n",
       "      <td>0.86</td>\n",
       "      <td>1.06</td>\n",
       "      <td>...</td>\n",
       "      <td>0.84</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.71</td>\n",
       "      <td>1.42</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-01</th>\n",
       "      <td>45.94</td>\n",
       "      <td>6.53</td>\n",
       "      <td>6.97</td>\n",
       "      <td>7.89</td>\n",
       "      <td>1.50</td>\n",
       "      <td>2.40</td>\n",
       "      <td>3.56</td>\n",
       "      <td>2.57</td>\n",
       "      <td>1.10</td>\n",
       "      <td>1.02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>60 rows × 29 columns</p>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "execution_count": 87
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "source": [
    "from matplotlib.ticker import MultipleLocator\r\n",
    "from matplotlib import font_manager\r\n",
    "font = font_manager.FontProperties(fname='C:/Windows/fonts/simkai.ttf')\r\n",
    "fig, axes = plt.subplots(1, 1, figsize=(8, 4))\r\n",
    "plt.plot(re_move_df)\r\n",
    "axes.yaxis.set_minor_locator(MultipleLocator(5))\r\n",
    "axes.xaxis.set_major_locator(MultipleLocator(base=5))\r\n",
    "axes.grid(which='minor', c='lightgrey')\r\n",
    "plt.legend(o_list, prop=font, loc='lower center',  bbox_to_anchor=(0.5, -1),\r\n",
    "           fancybox=True, shadow=True, ncol=3 )\r\n",
    "plt.title(label=\"BJ 2021 migrate-in percent\")\r\n",
    "plt.xticks(rotation=30)\r\n",
    "plt.show()\r\n"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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       "<Figure size 576x288 with 1 Axes>"
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"
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